Overview

Brought to you by YData

Dataset statistics

Number of variables29
Number of observations42903
Missing cells646844
Missing cells (%)52.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory76.1 MiB
Average record size in memory1.8 KiB

Variable types

Text21
Unsupported2
URL3
Categorical2
Numeric1

Alerts

country has constant value "United States" Constant
languages[9] has constant value "Arabic (North Levantine Spoken)" Constant
middle_name has 39483 (92.0%) missing values Missing
last_name has 1091 (2.5%) missing values Missing
office_name has 1399 (3.3%) missing values Missing
title has 42903 (100.0%) missing values Missing
description has 27692 (64.5%) missing values Missing
image_url has 6702 (15.6%) missing values Missing
agent_phone_numbers[0] has 4602 (10.7%) missing values Missing
agent_phone_numbers[1] has 35713 (83.2%) missing values Missing
email has 42903 (100.0%) missing values Missing
website has 30732 (71.6%) missing values Missing
languages[0] has 35773 (83.4%) missing values Missing
languages[1] has 36135 (84.2%) missing values Missing
languages[2] has 41787 (97.4%) missing values Missing
languages[3] has 42593 (99.3%) missing values Missing
languages[4] has 42836 (99.8%) missing values Missing
languages[5] has 42886 (> 99.9%) missing values Missing
languages[6] has 42899 (> 99.9%) missing values Missing
languages[7] has 42900 (> 99.9%) missing values Missing
languages[8] has 42901 (> 99.9%) missing values Missing
languages[9] has 42902 (> 99.9%) missing values Missing
_id has unique values Unique
profile_url has unique values Unique
title is an unsupported type, check if it needs cleaning or further analysis Unsupported
email is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2024-11-26 10:11:20.587395
Analysis finished2024-11-26 10:11:51.065999
Duration30.48 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

_id
Text

Unique 

Distinct42903
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.3 MiB
2024-11-26T15:41:51.784427image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters1029672
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42903 ?
Unique (%)100.0%

Sample

1st row674595d263f3d792c14081ce
2nd row674595d263f3d792c14081cf
3rd row674595d263f3d792c14081d0
4th row674595d263f3d792c14081d1
5th row674595d263f3d792c14081d2
ValueCountFrequency (%)
674595d263f3d792c14081ce 1
 
< 0.1%
674595d263f3d792c14081e2 1
 
< 0.1%
674595d263f3d792c14081e1 1
 
< 0.1%
674595d263f3d792c14081d0 1
 
< 0.1%
674595d263f3d792c14081d1 1
 
< 0.1%
674595d263f3d792c14081d2 1
 
< 0.1%
674595d263f3d792c14081d3 1
 
< 0.1%
674595d263f3d792c14081d4 1
 
< 0.1%
674595d263f3d792c14081d5 1
 
< 0.1%
674595d263f3d792c14081d6 1
 
< 0.1%
Other values (42893) 42893
> 99.9%
2024-11-26T15:41:53.215019image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 100917
9.8%
3 97895
9.5%
5 96992
9.4%
7 96975
9.4%
4 95992
9.3%
6 95980
9.3%
d 91368
8.9%
1 67576
 
6.6%
f 57929
 
5.6%
c 57914
 
5.6%
Other values (6) 170134
16.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1029672
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9 100917
9.8%
3 97895
9.5%
5 96992
9.4%
7 96975
9.4%
4 95992
9.3%
6 95980
9.3%
d 91368
8.9%
1 67576
 
6.6%
f 57929
 
5.6%
c 57914
 
5.6%
Other values (6) 170134
16.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1029672
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9 100917
9.8%
3 97895
9.5%
5 96992
9.4%
7 96975
9.4%
4 95992
9.3%
6 95980
9.3%
d 91368
8.9%
1 67576
 
6.6%
f 57929
 
5.6%
c 57914
 
5.6%
Other values (6) 170134
16.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1029672
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9 100917
9.8%
3 97895
9.5%
5 96992
9.4%
7 96975
9.4%
4 95992
9.3%
6 95980
9.3%
d 91368
8.9%
1 67576
 
6.6%
f 57929
 
5.6%
c 57914
 
5.6%
Other values (6) 170134
16.5%
Distinct8632
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2024-11-26T15:41:54.109723image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length59
Median length47
Mean length6.0919283
Min length1

Characters and Unicode

Total characters261362
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5589 ?
Unique (%)13.0%

Sample

1st rowKyle
2nd rowWilliam
3rd rowFermin
4th row21
5th rowThe
ValueCountFrequency (%)
the 943
 
2.0%
team 639
 
1.4%
michael 419
 
0.9%
david 353
 
0.8%
john 350
 
0.8%
jennifer 295
 
0.6%
lisa 271
 
0.6%
robert 261
 
0.6%
mary 243
 
0.5%
maria 238
 
0.5%
Other values (8416) 42249
91.3%
2024-11-26T15:41:55.808384image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 32394
 
12.4%
e 28275
 
10.8%
n 20315
 
7.8%
i 20233
 
7.7%
r 16860
 
6.5%
l 13055
 
5.0%
o 10671
 
4.1%
t 9204
 
3.5%
h 9050
 
3.5%
s 8534
 
3.3%
Other values (69) 92771
35.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 261362
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 32394
 
12.4%
e 28275
 
10.8%
n 20315
 
7.8%
i 20233
 
7.7%
r 16860
 
6.5%
l 13055
 
5.0%
o 10671
 
4.1%
t 9204
 
3.5%
h 9050
 
3.5%
s 8534
 
3.3%
Other values (69) 92771
35.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 261362
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 32394
 
12.4%
e 28275
 
10.8%
n 20315
 
7.8%
i 20233
 
7.7%
r 16860
 
6.5%
l 13055
 
5.0%
o 10671
 
4.1%
t 9204
 
3.5%
h 9050
 
3.5%
s 8534
 
3.3%
Other values (69) 92771
35.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 261362
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 32394
 
12.4%
e 28275
 
10.8%
n 20315
 
7.8%
i 20233
 
7.7%
r 16860
 
6.5%
l 13055
 
5.0%
o 10671
 
4.1%
t 9204
 
3.5%
h 9050
 
3.5%
s 8534
 
3.3%
Other values (69) 92771
35.5%

middle_name
Text

Missing 

Distinct1358
Distinct (%)39.7%
Missing39483
Missing (%)92.0%
Memory size1.4 MiB
2024-11-26T15:41:56.870826image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length18
Median length15
Mean length4.9883041
Min length1

Characters and Unicode

Total characters17060
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique885 ?
Unique (%)25.9%

Sample

1st rowMike
2nd rowMills
3rd rowElite
4th rowMcCatty
5th rowI.
ValueCountFrequency (%)
home 86
 
2.5%
a 68
 
2.0%
realty 66
 
1.9%
ann 64
 
1.9%
m 61
 
1.8%
j 49
 
1.4%
de 46
 
1.3%
l 44
 
1.3%
37
 
1.1%
roman 37
 
1.1%
Other values (1295) 2862
83.7%
2024-11-26T15:41:58.588627image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1888
 
11.1%
a 1429
 
8.4%
n 1117
 
6.5%
r 1104
 
6.5%
o 1097
 
6.4%
i 967
 
5.7%
l 897
 
5.3%
t 738
 
4.3%
s 597
 
3.5%
m 412
 
2.4%
Other values (52) 6814
39.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17060
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1888
 
11.1%
a 1429
 
8.4%
n 1117
 
6.5%
r 1104
 
6.5%
o 1097
 
6.4%
i 967
 
5.7%
l 897
 
5.3%
t 738
 
4.3%
s 597
 
3.5%
m 412
 
2.4%
Other values (52) 6814
39.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17060
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1888
 
11.1%
a 1429
 
8.4%
n 1117
 
6.5%
r 1104
 
6.5%
o 1097
 
6.4%
i 967
 
5.7%
l 897
 
5.3%
t 738
 
4.3%
s 597
 
3.5%
m 412
 
2.4%
Other values (52) 6814
39.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17060
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1888
 
11.1%
a 1429
 
8.4%
n 1117
 
6.5%
r 1104
 
6.5%
o 1097
 
6.4%
i 967
 
5.7%
l 897
 
5.3%
t 738
 
4.3%
s 597
 
3.5%
m 412
 
2.4%
Other values (52) 6814
39.9%

last_name
Text

Missing 

Distinct19186
Distinct (%)45.9%
Missing1091
Missing (%)2.5%
Memory size2.6 MiB
2024-11-26T15:41:59.549405image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length22
Median length20
Mean length6.4186836
Min length1

Characters and Unicode

Total characters268378
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14296 ?
Unique (%)34.2%

Sample

1st rowSeyboth
2nd rowLublin
3rd rowGroup
4th rowTeam
5th rowGroup
ValueCountFrequency (%)
team 886
 
2.1%
group 480
 
1.1%
smith 272
 
0.7%
johnson 222
 
0.5%
jr 213
 
0.5%
williams 180
 
0.4%
brown 161
 
0.4%
jones 157
 
0.4%
garcia 143
 
0.3%
miller 121
 
0.3%
Other values (18871) 38977
93.2%
2024-11-26T15:42:00.951966image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 26892
 
10.0%
a 25339
 
9.4%
r 20506
 
7.6%
o 19009
 
7.1%
n 18855
 
7.0%
i 15897
 
5.9%
l 14853
 
5.5%
s 12360
 
4.6%
t 9876
 
3.7%
u 7032
 
2.6%
Other values (60) 97759
36.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 268378
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 26892
 
10.0%
a 25339
 
9.4%
r 20506
 
7.6%
o 19009
 
7.1%
n 18855
 
7.0%
i 15897
 
5.9%
l 14853
 
5.5%
s 12360
 
4.6%
t 9876
 
3.7%
u 7032
 
2.6%
Other values (60) 97759
36.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 268378
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 26892
 
10.0%
a 25339
 
9.4%
r 20506
 
7.6%
o 19009
 
7.1%
n 18855
 
7.0%
i 15897
 
5.9%
l 14853
 
5.5%
s 12360
 
4.6%
t 9876
 
3.7%
u 7032
 
2.6%
Other values (60) 97759
36.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 268378
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 26892
 
10.0%
a 25339
 
9.4%
r 20506
 
7.6%
o 19009
 
7.1%
n 18855
 
7.0%
i 15897
 
5.9%
l 14853
 
5.5%
s 12360
 
4.6%
t 9876
 
3.7%
u 7032
 
2.6%
Other values (60) 97759
36.4%

office_name
Text

Missing 

Distinct873
Distinct (%)2.1%
Missing1399
Missing (%)3.3%
Memory size2.9 MiB
2024-11-26T15:42:01.819663image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length44
Median length30
Mean length14.279347
Min length3

Characters and Unicode

Total characters592650
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)< 0.1%

Sample

1st rowThe Seyboth Team
2nd rowAdvantage Gold
3rd rowNorth East
4th rowHomeStar
5th rowBarefoot Realty
ValueCountFrequency (%)
realty 14110
 
15.6%
real 3490
 
3.8%
estate 3490
 
3.8%
3297
 
3.6%
inc 3266
 
3.6%
company 1846
 
2.0%
group 1578
 
1.7%
north 1332
 
1.5%
alliance 1290
 
1.4%
associates 1227
 
1.4%
Other values (840) 55742
61.5%
2024-11-26T15:42:03.466044image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 65827
 
11.1%
49164
 
8.3%
a 47543
 
8.0%
t 46282
 
7.8%
l 37735
 
6.4%
r 28912
 
4.9%
o 28524
 
4.8%
s 28371
 
4.8%
n 27910
 
4.7%
i 26300
 
4.4%
Other values (57) 206082
34.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 592650
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 65827
 
11.1%
49164
 
8.3%
a 47543
 
8.0%
t 46282
 
7.8%
l 37735
 
6.4%
r 28912
 
4.9%
o 28524
 
4.8%
s 28371
 
4.8%
n 27910
 
4.7%
i 26300
 
4.4%
Other values (57) 206082
34.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 592650
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 65827
 
11.1%
49164
 
8.3%
a 47543
 
8.0%
t 46282
 
7.8%
l 37735
 
6.4%
r 28912
 
4.9%
o 28524
 
4.8%
s 28371
 
4.8%
n 27910
 
4.7%
i 26300
 
4.4%
Other values (57) 206082
34.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 592650
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 65827
 
11.1%
49164
 
8.3%
a 47543
 
8.0%
t 46282
 
7.8%
l 37735
 
6.4%
r 28912
 
4.9%
o 28524
 
4.8%
s 28371
 
4.8%
n 27910
 
4.7%
i 26300
 
4.4%
Other values (57) 206082
34.8%

title
Unsupported

Missing  Rejected  Unsupported 

Missing42903
Missing (%)100.0%
Memory size335.3 KiB

description
Text

Missing 

Distinct13983
Distinct (%)91.9%
Missing27692
Missing (%)64.5%
Memory size15.3 MiB
2024-11-26T15:42:04.474797image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length6609
Median length2178
Mean length937.78075
Min length26

Characters and Unicode

Total characters14264583
Distinct characters92
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13743 ?
Unique (%)90.3%

Sample

1st row1997 GPAR REALTOR of the Year Inducted to Greater Phila. Association of REALTORS Hall of Fame Certified Real Estate Instructor BILL LUBLIN operates a successful multi-office real estate firm and has been recognized as a thought leader for his insights regarding technology and its use in business. An international speaker and trainer, he makes complicated things simple in a fast paced entertaining manner. Entering the real estate business in 1971 at the age of 21, Bill rapidly gained recognition as one of the best salespeople in the marketplace. From his earliest days he began a career of service to both the community and the industry, always embracing the latest tools and technology. Bill has served as a member of the National Association of REALTORS Professional Standards Committee and Risk Management Committee. He was also appointed to serve on the Interpretations and Procedures Sub-Committee, the Article 10 Standards Revision Working Group, the Commercial Membership Recruitment Group, the BPO Workgroup, and was appointed Chair of the NAR Short Sale Workgroup. In addition Bill has was Vice-Chair of the Professional Standards Forum and the Professional Standards Committee, was Chairman of the Committee in 2008, the Association's Centennial Year, and chairing the Interpretations and Procedures Sub-Committee of Professional Standards in 2009 . In 2014 Bill will serve as the Chair for the MLS Issues & Policies Committee for NAR.
2nd rowLexington is where Tim Williams, owner and broker-in-charge at 803 Realty , grew up. 803 Realty offers a stress-free approach to buying and selling real estate through partnerships with industry leaders throughout the purchasing or selling process. These partnerships and connections allow clients to feel at ease and know that every step of the process is being held with the utmost care and urgency. The agency has also partnered with a property management company that allows for their clients to have a one stop approach to real estate. 803 Realty rebranded in June of 2020, after first opening its doors as Williams Real Estate Group in January 2016 as a full service residential real estate company. Tim and the other 42 agents pride themselves on their VIP client level customer service. They are selling homes 25 days faster than the Midlands average and operate as a one stop shop for both real estate sales and rentals. Tim is continually expanding to service communities throughout the 803 area code. He recently announced the expansion of their sales force to the Aiken/North Augusta market. The agency continues to focus on finding new ways to serve the community by joining multiple charitable foundations and business leaders that work to beautify the town and encourage growth and diversity. Everyday, Tim gets to help individuals and families with one of the largest purchases of their life, real estate. Not only that, but he also gets to mentor agents who work with 803 Realty and learn new ways to serve the community and build the business. Tim is grateful how his work in this service industry has touched his life. He shared that life is a beautiful thing that we must all be grateful for and that success should be defined by the individual, not a company or corporation. I feel as though in this industry and in any 'luxury industry' there is too much pressure on agents to work towards driving a certain car or making a certain amount of money, he said. We all have different levels of comfort when it comes to living and different things we are working toward. I feel as though it's important as a company that we promote that individuality because that's what makes this community thrive and great. 803 Realty will always remain locally owned and operated, putting their clients and community first. Visit 803 Realty at 5599 Sunset Boulevard or at www.803realtylexington.com . Tim and his wife Cidney, are quite involved in Lexington, from helping out at the schools their four children attend to taking part in city beautification projects. They also love Lake Murray - the jewel of South Carolina. I love time with my family and vacationing, Tim adds. They are the center of my world.
3rd rowShelly Garner is a local Realtor with 24 years experience in the Lexington and Columbia Area. Shelly has ranked in the Real Trends Top 1,000 agents nationally for the past 4 years. Shelly has a real passion for new homes sales and over the past 8 years has been honored to have achieved being the top sales agent for a local builder. Shelly is committed to helping you buy or sell your home with the highest level of expertise in your local market. Shelly creates a positive experience for both sides in any real estate transaction. Known by clients and colleagues alike for her honesty, perseverance and professionalism, she has a reputation for a quick, timely response to each client's needs and concerns. Shelly has the market knowledge as well as negotiation and communication skills to provide exceptional customer satisfaction, which is her personal commitment to each and every client. Give Shelly a Call or Email she would love to assist you with your real estate needs.
4th row#1 Century 21 Realtor in The United States #1 Century 21 realtor in Oklahoma for the past 5 years #1 Realtor in Tahlequah Best of the Best for the past several years #1 in Customer Service for the past 5 years ABR, SRS, CRS, GRI, CHMS A Home SOLD Every 2.1 days
5th rowMike and Melanie Scheetz began serving the greater Indianapolis area residential real estate community over two decades ago in 1995. With over 20 years of experience and the beneficial insight of a male and female team, Mike and Melanie offer service that is set apart from the rest with their unparalleled knowledge, experience, and insightful expertise. Choosing Mike and Melanie Scheetz will not only provide a stress-free buying and selling experience, but a lasting relationship with people who care more about the relationships they'll build than the commission they'll earn.
ValueCountFrequency (%)
and 100406
 
4.2%
the 83794
 
3.5%
to 73301
 
3.1%
a 61727
 
2.6%
in 56542
 
2.4%
of 55378
 
2.3%
i 48238
 
2.0%
real 33157
 
1.4%
estate 32979
 
1.4%
with 32562
 
1.4%
Other values (41678) 1801656
75.7%
2024-11-26T15:42:06.341340image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2364529
16.6%
e 1440598
 
10.1%
a 930188
 
6.5%
t 905384
 
6.3%
n 833586
 
5.8%
o 828729
 
5.8%
i 821575
 
5.8%
r 746152
 
5.2%
s 721746
 
5.1%
l 503771
 
3.5%
Other values (82) 4168325
29.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14264583
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2364529
16.6%
e 1440598
 
10.1%
a 930188
 
6.5%
t 905384
 
6.3%
n 833586
 
5.8%
o 828729
 
5.8%
i 821575
 
5.8%
r 746152
 
5.2%
s 721746
 
5.1%
l 503771
 
3.5%
Other values (82) 4168325
29.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14264583
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2364529
16.6%
e 1440598
 
10.1%
a 930188
 
6.5%
t 905384
 
6.3%
n 833586
 
5.8%
o 828729
 
5.8%
i 821575
 
5.8%
r 746152
 
5.2%
s 721746
 
5.1%
l 503771
 
3.5%
Other values (82) 4168325
29.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14264583
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2364529
16.6%
e 1440598
 
10.1%
a 930188
 
6.5%
t 905384
 
6.3%
n 833586
 
5.8%
o 828729
 
5.8%
i 821575
 
5.8%
r 746152
 
5.2%
s 721746
 
5.1%
l 503771
 
3.5%
Other values (82) 4168325
29.2%

image_url
URL

Missing 

Distinct34891
Distinct (%)96.4%
Missing6702
Missing (%)15.6%
Memory size7.6 MiB
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/67c/150/90/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvczNoazhiN25kZGF2NG5wcHNyMzRtdm1wcDJp.jpg
 
37
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/55e/8aa/2d/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvN2MwYThnOTlxemoxbXhhdDJ4MGdqYzBiMjBp.jpg
 
29
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/a79/eb5/a5/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xaTAvcG42Z2VyeHR2aHo0NGR5YTZ4ZDR3cTl5ajRp.jpg
 
28
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/4fd/955/a1/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvZHZ0OHR6MGpkZmRuNGt0dGh0N2RhNXpuZTZp.jpg
 
22
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/97a/a37/ed/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvYWNhZGtkZmY0ejk2bXM2bmF5ZTFlN2hnOTdp.jpg
 
22
Other values (34886)
36063 
(Missing)
6702 
ValueCountFrequency (%)
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/67c/150/90/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvczNoazhiN25kZGF2NG5wcHNyMzRtdm1wcDJp.jpg 37
 
0.1%
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/55e/8aa/2d/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvN2MwYThnOTlxemoxbXhhdDJ4MGdqYzBiMjBp.jpg 29
 
0.1%
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/a79/eb5/a5/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xaTAvcG42Z2VyeHR2aHo0NGR5YTZ4ZDR3cTl5ajRp.jpg 28
 
0.1%
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/4fd/955/a1/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvZHZ0OHR6MGpkZmRuNGt0dGh0N2RhNXpuZTZp.jpg 22
 
0.1%
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/97a/a37/ed/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvYWNhZGtkZmY0ejk2bXM2bmF5ZTFlN2hnOTdp.jpg 22
 
0.1%
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/011/468/82/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvYWdiMDRhc2F5NDdlbXNqMGdzbjJnNmdqNzJp.jpg 20
 
< 0.1%
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/d1f/a93/eb/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvMWZ5Z2NyNjF6aGh0bTl0ZHI3MzM0czc3ZDdp.jpg 20
 
< 0.1%
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/7dd/dea/fa/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvc2I2YWJhZnR5Ynh2NHR0YXg2ZmtrYjhrcjZp.jpg 19
 
< 0.1%
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/d65/717/f9/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvcGV2aGJhcmQ0dDJkbXYyeDQ0dzFkYTA5ZTFp.jpg 16
 
< 0.1%
https://www.century21.com/c21/remote-media/affiliate-4x5-316w/ea3/117/58/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvcTRwMDkyYWo0ZHlubWsyd3IzNXdnanl6cTRp.jpg 15
 
< 0.1%
Other values (34881) 35973
83.8%
(Missing) 6702
 
15.6%
ValueCountFrequency (%)
https 36201
84.4%
(Missing) 6702
 
15.6%
ValueCountFrequency (%)
www.century21.com 36201
84.4%
(Missing) 6702
 
15.6%
ValueCountFrequency (%)
/c21/remote-media/affiliate-4x5-316w/67c/150/90/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvczNoazhiN25kZGF2NG5wcHNyMzRtdm1wcDJp.jpg 37
 
0.1%
/c21/remote-media/affiliate-4x5-316w/55e/8aa/2d/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvN2MwYThnOTlxemoxbXhhdDJ4MGdqYzBiMjBp.jpg 29
 
0.1%
/c21/remote-media/affiliate-4x5-316w/a79/eb5/a5/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xaTAvcG42Z2VyeHR2aHo0NGR5YTZ4ZDR3cTl5ajRp.jpg 28
 
0.1%
/c21/remote-media/affiliate-4x5-316w/4fd/955/a1/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvZHZ0OHR6MGpkZmRuNGt0dGh0N2RhNXpuZTZp.jpg 22
 
0.1%
/c21/remote-media/affiliate-4x5-316w/97a/a37/ed/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvYWNhZGtkZmY0ejk2bXM2bmF5ZTFlN2hnOTdp.jpg 22
 
0.1%
/c21/remote-media/affiliate-4x5-316w/011/468/82/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvYWdiMDRhc2F5NDdlbXNqMGdzbjJnNmdqNzJp.jpg 20
 
< 0.1%
/c21/remote-media/affiliate-4x5-316w/d1f/a93/eb/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvMWZ5Z2NyNjF6aGh0bTl0ZHI3MzM0czc3ZDdp.jpg 20
 
< 0.1%
/c21/remote-media/affiliate-4x5-316w/7dd/dea/fa/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvc2I2YWJhZnR5Ynh2NHR0YXg2ZmtrYjhrcjZp.jpg 19
 
< 0.1%
/c21/remote-media/affiliate-4x5-316w/d65/717/f9/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvcGV2aGJhcmQ0dDJkbXYyeDQ0dzFkYTA5ZTFp.jpg 16
 
< 0.1%
/c21/remote-media/affiliate-4x5-316w/ea3/117/58/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvcTRwMDkyYWo0ZHlubWsyd3IzNXdnanl6cTRp.jpg 15
 
< 0.1%
Other values (34881) 35973
83.8%
(Missing) 6702
 
15.6%
ValueCountFrequency (%)
36201
84.4%
(Missing) 6702
 
15.6%
ValueCountFrequency (%)
36201
84.4%
(Missing) 6702
 
15.6%
Distinct1651
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size3.2 MiB
2024-11-26T15:42:07.398717image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length40
Median length35
Mean length20.005244
Min length8

Characters and Unicode

Total characters858285
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)0.1%

Sample

1st row969 Waterman Ave
2nd row494 Second Street Pike
3rd row130 Parker St
4th row31320 Solon Road
5th row4720 Barefoot Resort Bridge Road
ValueCountFrequency (%)
street 7389
 
4.7%
road 6453
 
4.1%
avenue 4256
 
2.7%
blvd 3623
 
2.3%
drive 2990
 
1.9%
ave 2881
 
1.8%
main 2604
 
1.6%
rd 2406
 
1.5%
suite 2378
 
1.5%
s 2283
 
1.4%
Other values (2327) 120720
76.4%
2024-11-26T15:42:09.247745image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
115080
 
13.4%
e 68546
 
8.0%
a 43298
 
5.0%
t 41716
 
4.9%
r 37684
 
4.4%
1 34121
 
4.0%
o 33732
 
3.9%
0 30266
 
3.5%
n 28403
 
3.3%
i 27946
 
3.3%
Other values (60) 397493
46.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 858285
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
115080
 
13.4%
e 68546
 
8.0%
a 43298
 
5.0%
t 41716
 
4.9%
r 37684
 
4.4%
1 34121
 
4.0%
o 33732
 
3.9%
0 30266
 
3.5%
n 28403
 
3.3%
i 27946
 
3.3%
Other values (60) 397493
46.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 858285
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
115080
 
13.4%
e 68546
 
8.0%
a 43298
 
5.0%
t 41716
 
4.9%
r 37684
 
4.4%
1 34121
 
4.0%
o 33732
 
3.9%
0 30266
 
3.5%
n 28403
 
3.3%
i 27946
 
3.3%
Other values (60) 397493
46.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 858285
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
115080
 
13.4%
e 68546
 
8.0%
a 43298
 
5.0%
t 41716
 
4.9%
r 37684
 
4.4%
1 34121
 
4.0%
o 33732
 
3.9%
0 30266
 
3.5%
n 28403
 
3.3%
i 27946
 
3.3%
Other values (60) 397493
46.3%

city
Text

Distinct1300
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.7 MiB
2024-11-26T15:42:10.089181image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length22
Median length18
Mean length9.2018507
Min length3

Characters and Unicode

Total characters394787
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)0.1%

Sample

1st rowEast Providence
2nd rowSouthampton
3rd rowLawrence
4th rowSolon
5th rowNorth Myrtle Beach
ValueCountFrequency (%)
beach 1528
 
2.7%
city 914
 
1.6%
san 843
 
1.5%
fort 671
 
1.2%
heights 565
 
1.0%
solon 483
 
0.8%
park 418
 
0.7%
hills 403
 
0.7%
wayne 398
 
0.7%
springs 388
 
0.7%
Other values (1302) 50299
88.4%
2024-11-26T15:42:11.859455image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 35442
 
9.0%
a 35155
 
8.9%
o 31593
 
8.0%
n 28312
 
7.2%
r 26104
 
6.6%
l 25895
 
6.6%
i 24064
 
6.1%
t 18762
 
4.8%
s 16242
 
4.1%
14007
 
3.5%
Other values (44) 139211
35.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 394787
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 35442
 
9.0%
a 35155
 
8.9%
o 31593
 
8.0%
n 28312
 
7.2%
r 26104
 
6.6%
l 25895
 
6.6%
i 24064
 
6.1%
t 18762
 
4.8%
s 16242
 
4.1%
14007
 
3.5%
Other values (44) 139211
35.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 394787
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 35442
 
9.0%
a 35155
 
8.9%
o 31593
 
8.0%
n 28312
 
7.2%
r 26104
 
6.6%
l 25895
 
6.6%
i 24064
 
6.1%
t 18762
 
4.8%
s 16242
 
4.1%
14007
 
3.5%
Other values (44) 139211
35.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 394787
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 35442
 
9.0%
a 35155
 
8.9%
o 31593
 
8.0%
n 28312
 
7.2%
r 26104
 
6.6%
l 25895
 
6.6%
i 24064
 
6.1%
t 18762
 
4.8%
s 16242
 
4.1%
14007
 
3.5%
Other values (44) 139211
35.3%

state
Text

Distinct52
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-11-26T15:42:12.501204image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters85806
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRI
2nd rowPA
3rd rowMA
4th rowOH
5th rowSC
ValueCountFrequency (%)
ca 7011
16.3%
fl 4754
 
11.1%
tx 2724
 
6.3%
nj 2560
 
6.0%
ny 2157
 
5.0%
mi 1574
 
3.7%
il 1539
 
3.6%
ga 1397
 
3.3%
oh 1351
 
3.1%
pa 1333
 
3.1%
Other values (42) 16503
38.5%
2024-11-26T15:42:13.781920image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 14932
17.4%
C 9674
11.3%
N 8710
10.2%
L 7095
 
8.3%
I 6187
 
7.2%
T 5040
 
5.9%
M 4905
 
5.7%
F 4754
 
5.5%
X 2724
 
3.2%
Y 2638
 
3.1%
Other values (14) 19147
22.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 85806
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 14932
17.4%
C 9674
11.3%
N 8710
10.2%
L 7095
 
8.3%
I 6187
 
7.2%
T 5040
 
5.9%
M 4905
 
5.7%
F 4754
 
5.5%
X 2724
 
3.2%
Y 2638
 
3.1%
Other values (14) 19147
22.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 85806
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 14932
17.4%
C 9674
11.3%
N 8710
10.2%
L 7095
 
8.3%
I 6187
 
7.2%
T 5040
 
5.9%
M 4905
 
5.7%
F 4754
 
5.5%
X 2724
 
3.2%
Y 2638
 
3.1%
Other values (14) 19147
22.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 85806
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 14932
17.4%
C 9674
11.3%
N 8710
10.2%
L 7095
 
8.3%
I 6187
 
7.2%
T 5040
 
5.9%
M 4905
 
5.7%
F 4754
 
5.5%
X 2724
 
3.2%
Y 2638
 
3.1%
Other values (14) 19147
22.3%

country
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
United States
42903 

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters557739
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnited States
2nd rowUnited States
3rd rowUnited States
4th rowUnited States
5th rowUnited States

Common Values

ValueCountFrequency (%)
United States 42903
100.0%

Length

2024-11-26T15:42:14.480253image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-26T15:42:15.073017image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
ValueCountFrequency (%)
united 42903
50.0%
states 42903
50.0%

Most occurring characters

ValueCountFrequency (%)
t 128709
23.1%
e 85806
15.4%
U 42903
 
7.7%
n 42903
 
7.7%
i 42903
 
7.7%
d 42903
 
7.7%
42903
 
7.7%
S 42903
 
7.7%
a 42903
 
7.7%
s 42903
 
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 557739
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 128709
23.1%
e 85806
15.4%
U 42903
 
7.7%
n 42903
 
7.7%
i 42903
 
7.7%
d 42903
 
7.7%
42903
 
7.7%
S 42903
 
7.7%
a 42903
 
7.7%
s 42903
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 557739
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 128709
23.1%
e 85806
15.4%
U 42903
 
7.7%
n 42903
 
7.7%
i 42903
 
7.7%
d 42903
 
7.7%
42903
 
7.7%
S 42903
 
7.7%
a 42903
 
7.7%
s 42903
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 557739
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 128709
23.1%
e 85806
15.4%
U 42903
 
7.7%
n 42903
 
7.7%
i 42903
 
7.7%
d 42903
 
7.7%
42903
 
7.7%
S 42903
 
7.7%
a 42903
 
7.7%
s 42903
 
7.7%

zipcode
Real number (ℝ)

Distinct1573
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49402.247
Minimum1201
Maximum99705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.3 KiB
2024-11-26T15:42:15.768734image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1201
5-th percentile6107
Q123464
median44139
Q378626
95-th percentile95010
Maximum99705
Range98504
Interquartile range (IQR)55162

Descriptive statistics

Standard deviation30757.506
Coefficient of variation (CV)0.62259325
Kurtosis-1.3428488
Mean49402.247
Median Absolute Deviation (MAD)27883
Skewness0.14618793
Sum2.1195046 × 109
Variance9.4602416 × 108
MonotonicityNot monotonic
2024-11-26T15:42:16.501306image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44139 483
 
1.1%
30041 385
 
0.9%
33708 382
 
0.9%
90660 368
 
0.9%
46825 342
 
0.8%
84047 334
 
0.8%
30076 306
 
0.7%
90505 259
 
0.6%
90703 225
 
0.5%
90240 220
 
0.5%
Other values (1563) 39599
92.3%
ValueCountFrequency (%)
1201 3
 
< 0.1%
1453 12
 
< 0.1%
1463 7
 
< 0.1%
1501 50
0.1%
1545 3
 
< 0.1%
1562 27
0.1%
1564 3
 
< 0.1%
1581 20
 
< 0.1%
1603 7
 
< 0.1%
1748 6
 
< 0.1%
ValueCountFrequency (%)
99705 9
 
< 0.1%
99701 5
 
< 0.1%
99669 26
0.1%
99645 3
 
< 0.1%
99577 6
 
< 0.1%
99515 16
 
< 0.1%
99352 63
0.1%
99201 55
0.1%
99114 16
 
< 0.1%
98926 15
 
< 0.1%
Distinct1531
Distinct (%)3.6%
Missing12
Missing (%)< 0.1%
Memory size2.9 MiB
2024-11-26T15:42:17.379482image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters600474
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)0.1%

Sample

1st row(401) 477-0124
2nd row(215) 671-4701
3rd row(800) 844-7653
4th row(440) 449-9100
5th row(843) 390-1999
ValueCountFrequency (%)
800 1781
 
2.1%
562 1189
 
1.4%
844-7653 994
 
1.2%
909 802
 
0.9%
770 769
 
0.9%
888 732
 
0.9%
440 676
 
0.8%
817 666
 
0.8%
732 647
 
0.8%
862-1194 617
 
0.7%
Other values (1765) 76909
89.7%
2024-11-26T15:42:18.641583image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 67472
11.2%
2 49293
 
8.2%
( 42891
 
7.1%
) 42891
 
7.1%
42891
 
7.1%
- 42891
 
7.1%
7 42852
 
7.1%
1 42349
 
7.1%
8 41515
 
6.9%
3 38143
 
6.4%
Other values (4) 147286
24.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 600474
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 67472
11.2%
2 49293
 
8.2%
( 42891
 
7.1%
) 42891
 
7.1%
42891
 
7.1%
- 42891
 
7.1%
7 42852
 
7.1%
1 42349
 
7.1%
8 41515
 
6.9%
3 38143
 
6.4%
Other values (4) 147286
24.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 600474
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 67472
11.2%
2 49293
 
8.2%
( 42891
 
7.1%
) 42891
 
7.1%
42891
 
7.1%
- 42891
 
7.1%
7 42852
 
7.1%
1 42349
 
7.1%
8 41515
 
6.9%
3 38143
 
6.4%
Other values (4) 147286
24.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 600474
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 67472
11.2%
2 49293
 
8.2%
( 42891
 
7.1%
) 42891
 
7.1%
42891
 
7.1%
- 42891
 
7.1%
7 42852
 
7.1%
1 42349
 
7.1%
8 41515
 
6.9%
3 38143
 
6.4%
Other values (4) 147286
24.5%
Distinct33453
Distinct (%)87.3%
Missing4602
Missing (%)10.7%
Memory size2.7 MiB
2024-11-26T15:42:19.751148image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.9894
Min length1

Characters and Unicode

Total characters535808
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31971 ?
Unique (%)83.5%

Sample

1st row(508) 726-3492
2nd row(215) 280-4114
3rd row(978) 423-6545
4th row(216) 373-7727
5th row(843) 213-8754
ValueCountFrequency (%)
562 666
 
0.9%
909 586
 
0.8%
732 486
 
0.6%
727 478
 
0.6%
703 457
 
0.6%
813 434
 
0.6%
817 425
 
0.6%
973 418
 
0.5%
626 414
 
0.5%
609 370
 
0.5%
Other values (33699) 71808
93.8%
2024-11-26T15:42:21.193973image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44580
 
8.3%
2 41429
 
7.7%
7 39745
 
7.4%
3 38785
 
7.2%
( 38241
 
7.1%
) 38241
 
7.1%
38241
 
7.1%
- 38241
 
7.1%
1 37003
 
6.9%
8 36865
 
6.9%
Other values (4) 144437
27.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 535808
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 44580
 
8.3%
2 41429
 
7.7%
7 39745
 
7.4%
3 38785
 
7.2%
( 38241
 
7.1%
) 38241
 
7.1%
38241
 
7.1%
- 38241
 
7.1%
1 37003
 
6.9%
8 36865
 
6.9%
Other values (4) 144437
27.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 535808
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 44580
 
8.3%
2 41429
 
7.7%
7 39745
 
7.4%
3 38785
 
7.2%
( 38241
 
7.1%
) 38241
 
7.1%
38241
 
7.1%
- 38241
 
7.1%
1 37003
 
6.9%
8 36865
 
6.9%
Other values (4) 144437
27.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 535808
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 44580
 
8.3%
2 41429
 
7.7%
7 39745
 
7.4%
3 38785
 
7.2%
( 38241
 
7.1%
) 38241
 
7.1%
38241
 
7.1%
- 38241
 
7.1%
1 37003
 
6.9%
8 36865
 
6.9%
Other values (4) 144437
27.0%
Distinct4384
Distinct (%)61.0%
Missing35713
Missing (%)83.2%
Memory size1.6 MiB
2024-11-26T15:42:22.126358image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.977191
Min length1

Characters and Unicode

Total characters100496
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3818 ?
Unique (%)53.1%

Sample

1st row(317) 814-2100
2nd row(410) 547-1116
3rd row(435) 705-3029
4th row(570) 265-2100
5th row(482) 000-1118
ValueCountFrequency (%)
703 286
 
2.0%
973 211
 
1.5%
301 194
 
1.4%
410 167
 
1.2%
562 154
 
1.1%
540 130
 
0.9%
570 120
 
0.8%
610 119
 
0.8%
732 112
 
0.8%
845 106
 
0.7%
Other values (4655) 12763
88.9%
2024-11-26T15:42:23.866076image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9960
 
9.9%
2 8273
 
8.2%
7 7238
 
7.2%
( 7172
 
7.1%
) 7172
 
7.1%
7172
 
7.1%
- 7172
 
7.1%
1 7161
 
7.1%
3 7022
 
7.0%
5 6783
 
6.7%
Other values (4) 25371
25.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 100496
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 9960
 
9.9%
2 8273
 
8.2%
7 7238
 
7.2%
( 7172
 
7.1%
) 7172
 
7.1%
7172
 
7.1%
- 7172
 
7.1%
1 7161
 
7.1%
3 7022
 
7.0%
5 6783
 
6.7%
Other values (4) 25371
25.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 100496
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 9960
 
9.9%
2 8273
 
8.2%
7 7238
 
7.2%
( 7172
 
7.1%
) 7172
 
7.1%
7172
 
7.1%
- 7172
 
7.1%
1 7161
 
7.1%
3 7022
 
7.0%
5 6783
 
6.7%
Other values (4) 25371
25.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 100496
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 9960
 
9.9%
2 8273
 
8.2%
7 7238
 
7.2%
( 7172
 
7.1%
) 7172
 
7.1%
7172
 
7.1%
- 7172
 
7.1%
1 7161
 
7.1%
3 7022
 
7.0%
5 6783
 
6.7%
Other values (4) 25371
25.2%

email
Unsupported

Missing  Rejected  Unsupported 

Missing42903
Missing (%)100.0%
Memory size335.3 KiB

website
URL

Missing 

Distinct10366
Distinct (%)85.2%
Missing30732
Missing (%)71.6%
Memory size2.1 MiB
https://century21cariotirealestate.com/
 
116
https://investmentrealty.sites.c21.homes/
 
49
http://www.century21broadhurst.com/
 
40
http://www.romanagents.com/
 
37
http://century21cedarcrest.com/
 
35
Other values (10361)
11894 
(Missing)
30732 
ValueCountFrequency (%)
https://century21cariotirealestate.com/ 116
 
0.3%
https://investmentrealty.sites.c21.homes/ 49
 
0.1%
http://www.century21broadhurst.com/ 40
 
0.1%
http://www.romanagents.com/ 37
 
0.1%
http://century21cedarcrest.com/ 35
 
0.1%
https://www.cariotisellsflorida.com/ 35
 
0.1%
https://alliancegroup.sites.c21.homes/ 29
 
0.1%
https://century21bono.com 29
 
0.1%
http://century21sbp.com/ 29
 
0.1%
https://c21adamsny.com 27
 
0.1%
Other values (10356) 11745
 
27.4%
(Missing) 30732
71.6%
ValueCountFrequency (%)
https 9148
 
21.3%
http 3023
 
7.0%
(Missing) 30732
71.6%
ValueCountFrequency (%)
c21affiliated.com 649
 
1.5%
www.century21.com 457
 
1.1%
homesforsale.century21.com 421
 
1.0%
www.viewmylisting.com 135
 
0.3%
www.c21bowman.com 123
 
0.3%
century21cariotirealestate.com 116
 
0.3%
search.c21ag.com 85
 
0.2%
affiliated.sites.c21.homes 77
 
0.2%
investmentrealty.sites.c21.homes 49
 
0.1%
www.century21broadhurst.com 42
 
0.1%
Other values (8166) 10017
 
23.3%
(Missing) 30732
71.6%
ValueCountFrequency (%)
/ 6418
 
15.0%
3561
 
8.3%
/real-estate-office/profile/century-21-royal-40000703 23
 
0.1%
/contact 4
 
< 0.1%
/century-21-geba-realty-4757c 4
 
< 0.1%
/agentdetail.cfm 4
 
< 0.1%
/real-estate-agents/profile/helms-rose-team-10005934 3
 
< 0.1%
/real-estate-agents/profile/tony-angela-the-medina-team-40001077 3
 
< 0.1%
//www.century21realty.com/ 3
 
< 0.1%
/agent/angela.averill@century21.com 3
 
< 0.1%
Other values (2134) 2145
 
5.0%
(Missing) 30732
71.6%
ValueCountFrequency (%)
12108
 
28.2%
k=1 15
 
< 0.1%
referredByCompany=4757 4
 
< 0.1%
ut 3
 
< 0.1%
oid=&chome=1&odoor= 3
 
< 0.1%
utm_ 2
 
< 0.1%
rvs=12 2
 
< 0.1%
utm_m 2
 
< 0.1%
utm_source=google&utm_medium=cpc&utm_campaign=residentialdiscovery&utm_term=&utm_content=&gclid=CjwKCAjwscGjBhAXEiwAswQqNMIZOxukZZEjkxd2bM9DXZdE0ujc0beu_70PMJ99Frg6j6ZphNtDRBoCZLoQAvD_BwE&gclsrc=aw.ds 2
 
< 0.1%
id=57 1
 
< 0.1%
Other values (29) 29
 
0.1%
(Missing) 30732
71.6%
ValueCountFrequency (%)
12169
 
28.4%
reviews 1
 
< 0.1%
/ 1
 
< 0.1%
(Missing) 30732
71.6%

profile_url
URL

Unique 

Distinct42903
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
https://www.century21.com/real-estate-agent/profile/kyle-seyboth-P80096892
 
1
https://www.century21.com/real-estate-agent/profile/marcy-david-P80187402
 
1
https://www.century21.com/real-estate-agent/profile/scott-davidson-P80168561
 
1
https://www.century21.com/real-estate-agent/profile/ben-davies-P80176702
 
1
https://www.century21.com/real-estate-agent/profile/tyler-davidson-P80072413
 
1
Other values (42898)
42898 
ValueCountFrequency (%)
https://www.century21.com/real-estate-agent/profile/kyle-seyboth-P80096892 1
 
< 0.1%
https://www.century21.com/real-estate-agent/profile/marcy-david-P80187402 1
 
< 0.1%
https://www.century21.com/real-estate-agent/profile/scott-davidson-P80168561 1
 
< 0.1%
https://www.century21.com/real-estate-agent/profile/ben-davies-P80176702 1
 
< 0.1%
https://www.century21.com/real-estate-agent/profile/tyler-davidson-P80072413 1
 
< 0.1%
https://www.century21.com/real-estate-agent/profile/dee-davies-P80136180 1
 
< 0.1%
https://www.century21.com/real-estate-agent/profile/beatriz-davila-P80187868 1
 
< 0.1%
https://www.century21.com/real-estate-agent/profile/michael-davila-P80134375 1
 
< 0.1%
https://www.century21.com/real-estate-agent/profile/alfreda-davis-P416539280 1
 
< 0.1%
https://www.century21.com/real-estate-agent/profile/alicia-davis-P80117851 1
 
< 0.1%
Other values (42893) 42893
> 99.9%
ValueCountFrequency (%)
https 42903
100.0%
ValueCountFrequency (%)
www.century21.com 42903
100.0%
ValueCountFrequency (%)
/real-estate-agent/profile/kyle-seyboth-P80096892 1
 
< 0.1%
/real-estate-agent/profile/marcy-david-P80187402 1
 
< 0.1%
/real-estate-agent/profile/scott-davidson-P80168561 1
 
< 0.1%
/real-estate-agent/profile/ben-davies-P80176702 1
 
< 0.1%
/real-estate-agent/profile/tyler-davidson-P80072413 1
 
< 0.1%
/real-estate-agent/profile/dee-davies-P80136180 1
 
< 0.1%
/real-estate-agent/profile/beatriz-davila-P80187868 1
 
< 0.1%
/real-estate-agent/profile/michael-davila-P80134375 1
 
< 0.1%
/real-estate-agent/profile/alfreda-davis-P416539280 1
 
< 0.1%
/real-estate-agent/profile/alicia-davis-P80117851 1
 
< 0.1%
Other values (42893) 42893
> 99.9%
ValueCountFrequency (%)
42903
100.0%
ValueCountFrequency (%)
42903
100.0%

languages[0]
Text

Missing 

Distinct104
Distinct (%)1.5%
Missing35773
Missing (%)83.4%
Memory size1.5 MiB
2024-11-26T15:42:24.601822image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length34
Median length7
Mean length7.3415147
Min length2

Characters and Unicode

Total characters52345
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)0.5%

Sample

1st rowSpanish
2nd rowEnglish
3rd rowEnglish
4th rowEnglish
5th rowFrench
ValueCountFrequency (%)
english 3452
46.4%
spanish 1810
24.3%
chinese 289
 
3.9%
hindi 178
 
2.4%
russian 138
 
1.9%
mandarin 131
 
1.8%
italian 116
 
1.6%
polish 112
 
1.5%
german 90
 
1.2%
arabic 88
 
1.2%
Other values (110) 1042
 
14.0%
2024-11-26T15:42:26.112916image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 7187
13.7%
i 7100
13.6%
s 6188
11.8%
h 5828
11.1%
l 3886
7.4%
g 3684
7.0%
a 3525
6.7%
E 3458
6.6%
p 1896
 
3.6%
S 1869
 
3.6%
Other values (43) 7724
14.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 52345
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 7187
13.7%
i 7100
13.6%
s 6188
11.8%
h 5828
11.1%
l 3886
7.4%
g 3684
7.0%
a 3525
6.7%
E 3458
6.6%
p 1896
 
3.6%
S 1869
 
3.6%
Other values (43) 7724
14.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 52345
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 7187
13.7%
i 7100
13.6%
s 6188
11.8%
h 5828
11.1%
l 3886
7.4%
g 3684
7.0%
a 3525
6.7%
E 3458
6.6%
p 1896
 
3.6%
S 1869
 
3.6%
Other values (43) 7724
14.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 52345
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 7187
13.7%
i 7100
13.6%
s 6188
11.8%
h 5828
11.1%
l 3886
7.4%
g 3684
7.0%
a 3525
6.7%
E 3458
6.6%
p 1896
 
3.6%
S 1869
 
3.6%
Other values (43) 7724
14.8%

languages[1]
Text

Missing 

Distinct95
Distinct (%)1.4%
Missing36135
Missing (%)84.2%
Memory size1.5 MiB
2024-11-26T15:42:26.814268image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length24
Median length7
Mean length7.3495863
Min length2

Characters and Unicode

Total characters49742
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)0.5%

Sample

1st rowEnglish
2nd rowArabic
3rd rowSpanish
4th rowArabic
5th rowEnglish
ValueCountFrequency (%)
english 2837
40.5%
spanish 2458
35.1%
arabic 180
 
2.6%
french 172
 
2.5%
chinese 163
 
2.3%
portuguese 102
 
1.5%
tagalog 94
 
1.3%
hindi 80
 
1.1%
russian 63
 
0.9%
italian 52
 
0.7%
Other values (95) 802
 
11.5%
2024-11-26T15:42:28.247420image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 6543
13.2%
i 6378
12.8%
s 5905
11.9%
h 5686
11.4%
a 3906
7.9%
g 3232
6.5%
l 3156
6.3%
E 2884
5.8%
S 2497
 
5.0%
p 2478
 
5.0%
Other values (41) 7077
14.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49742
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 6543
13.2%
i 6378
12.8%
s 5905
11.9%
h 5686
11.4%
a 3906
7.9%
g 3232
6.5%
l 3156
6.3%
E 2884
5.8%
S 2497
 
5.0%
p 2478
 
5.0%
Other values (41) 7077
14.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49742
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 6543
13.2%
i 6378
12.8%
s 5905
11.9%
h 5686
11.4%
a 3906
7.9%
g 3232
6.5%
l 3156
6.3%
E 2884
5.8%
S 2497
 
5.0%
p 2478
 
5.0%
Other values (41) 7077
14.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49742
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 6543
13.2%
i 6378
12.8%
s 5905
11.9%
h 5686
11.4%
a 3906
7.9%
g 3232
6.5%
l 3156
6.3%
E 2884
5.8%
S 2497
 
5.0%
p 2478
 
5.0%
Other values (41) 7077
14.2%

languages[2]
Text

Missing 

Distinct72
Distinct (%)6.5%
Missing41787
Missing (%)97.4%
Memory size1.3 MiB
2024-11-26T15:42:28.911978image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length31
Median length7
Mean length8.5448029
Min length3

Characters and Unicode

Total characters9536
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)2.4%

Sample

1st rowSpanish
2nd rowSpanish
3rd rowChinese (Yue/Cantonese)
4th rowSpanish
5th rowEnglish
ValueCountFrequency (%)
english 338
27.0%
spanish 139
11.1%
portuguese 117
 
9.3%
chinese 95
 
7.6%
french 76
 
6.1%
yue/cantonese 34
 
2.7%
punjabi 31
 
2.5%
eastern 31
 
2.5%
mandarin 30
 
2.4%
hindi 30
 
2.4%
Other values (69) 331
26.4%
2024-11-26T15:42:30.344478image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1094
11.5%
i 960
 
10.1%
s 848
 
8.9%
e 788
 
8.3%
h 674
 
7.1%
a 665
 
7.0%
g 520
 
5.5%
l 456
 
4.8%
r 417
 
4.4%
u 383
 
4.0%
Other values (40) 2731
28.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9536
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1094
11.5%
i 960
 
10.1%
s 848
 
8.9%
e 788
 
8.3%
h 674
 
7.1%
a 665
 
7.0%
g 520
 
5.5%
l 456
 
4.8%
r 417
 
4.4%
u 383
 
4.0%
Other values (40) 2731
28.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9536
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1094
11.5%
i 960
 
10.1%
s 848
 
8.9%
e 788
 
8.3%
h 674
 
7.1%
a 665
 
7.0%
g 520
 
5.5%
l 456
 
4.8%
r 417
 
4.4%
u 383
 
4.0%
Other values (40) 2731
28.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9536
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1094
11.5%
i 960
 
10.1%
s 848
 
8.9%
e 788
 
8.3%
h 674
 
7.1%
a 665
 
7.0%
g 520
 
5.5%
l 456
 
4.8%
r 417
 
4.4%
u 383
 
4.0%
Other values (40) 2731
28.6%

languages[3]
Text

Missing 

Distinct56
Distinct (%)18.1%
Missing42593
Missing (%)99.3%
Memory size1.3 MiB
2024-11-26T15:42:31.093588image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length23
Median length22
Mean length9.2677419
Min length3

Characters and Unicode

Total characters2873
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)7.7%

Sample

1st rowPortuguese
2nd rowEnglish
3rd rowRomanian
4th rowChinese (Mandarin)
5th rowSwedish
ValueCountFrequency (%)
english 72
19.4%
spanish 30
 
8.1%
chinese 29
 
7.8%
punjabi 20
 
5.4%
portuguese 19
 
5.1%
eastern 19
 
5.1%
hebrew 17
 
4.6%
mandarin 17
 
4.6%
yue/cantonese 9
 
2.4%
french 9
 
2.4%
Other values (56) 130
35.0%
2024-11-26T15:42:32.485296image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 337
 
11.7%
i 293
 
10.2%
a 271
 
9.4%
e 240
 
8.4%
s 212
 
7.4%
h 154
 
5.4%
r 140
 
4.9%
l 112
 
3.9%
g 106
 
3.7%
E 91
 
3.2%
Other values (40) 917
31.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2873
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 337
 
11.7%
i 293
 
10.2%
a 271
 
9.4%
e 240
 
8.4%
s 212
 
7.4%
h 154
 
5.4%
r 140
 
4.9%
l 112
 
3.9%
g 106
 
3.7%
E 91
 
3.2%
Other values (40) 917
31.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2873
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 337
 
11.7%
i 293
 
10.2%
a 271
 
9.4%
e 240
 
8.4%
s 212
 
7.4%
h 154
 
5.4%
r 140
 
4.9%
l 112
 
3.9%
g 106
 
3.7%
E 91
 
3.2%
Other values (40) 917
31.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2873
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 337
 
11.7%
i 293
 
10.2%
a 271
 
9.4%
e 240
 
8.4%
s 212
 
7.4%
h 154
 
5.4%
r 140
 
4.9%
l 112
 
3.9%
g 106
 
3.7%
E 91
 
3.2%
Other values (40) 917
31.9%

languages[4]
Categorical

Missing 

Distinct30
Distinct (%)44.8%
Missing42836
Missing (%)99.8%
Memory size1.6 MiB
Spanish
English
Urdu
Italian
Chinese (Mandarin)
 
3
Other values (25)
36 

Length

Max length23
Median length18
Mean length8.8656716
Min length3

Characters and Unicode

Total characters594
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)25.4%

Sample

1st rowChinese (Yue/Cantonese)
2nd rowEnglish
3rd rowItalian
4th rowPortuguese
5th rowSpanish

Common Values

ValueCountFrequency (%)
Spanish 9
 
< 0.1%
English 8
 
< 0.1%
Urdu 7
 
< 0.1%
Italian 4
 
< 0.1%
Chinese (Mandarin) 3
 
< 0.1%
Portuguese 3
 
< 0.1%
Serbian 3
 
< 0.1%
Armenian 3
 
< 0.1%
Khmer (Central) 2
 
< 0.1%
Persian 2
 
< 0.1%
Other values (20) 23
 
0.1%
(Missing) 42836
99.8%

Length

2024-11-26T15:42:33.286148image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
spanish 9
 
11.1%
english 8
 
9.9%
urdu 7
 
8.6%
chinese 6
 
7.4%
italian 4
 
4.9%
mandarin 3
 
3.7%
portuguese 3
 
3.7%
serbian 3
 
3.7%
armenian 3
 
3.7%
central 3
 
3.7%
Other values (26) 32
39.5%

Most occurring characters

ValueCountFrequency (%)
n 72
 
12.1%
a 68
 
11.4%
i 59
 
9.9%
e 45
 
7.6%
s 35
 
5.9%
r 35
 
5.9%
h 30
 
5.1%
l 22
 
3.7%
u 20
 
3.4%
t 17
 
2.9%
Other values (35) 191
32.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 594
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 72
 
12.1%
a 68
 
11.4%
i 59
 
9.9%
e 45
 
7.6%
s 35
 
5.9%
r 35
 
5.9%
h 30
 
5.1%
l 22
 
3.7%
u 20
 
3.4%
t 17
 
2.9%
Other values (35) 191
32.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 594
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 72
 
12.1%
a 68
 
11.4%
i 59
 
9.9%
e 45
 
7.6%
s 35
 
5.9%
r 35
 
5.9%
h 30
 
5.1%
l 22
 
3.7%
u 20
 
3.4%
t 17
 
2.9%
Other values (35) 191
32.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 594
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 72
 
12.1%
a 68
 
11.4%
i 59
 
9.9%
e 45
 
7.6%
s 35
 
5.9%
r 35
 
5.9%
h 30
 
5.1%
l 22
 
3.7%
u 20
 
3.4%
t 17
 
2.9%
Other values (35) 191
32.2%

languages[5]
Text

Missing 

Distinct15
Distinct (%)88.2%
Missing42886
Missing (%)> 99.9%
Memory size1.3 MiB
2024-11-26T15:42:33.905456image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length31
Median length10
Mean length9.1764706
Min length3

Characters and Unicode

Total characters156
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)76.5%

Sample

1st rowAlbanian
2nd rowPolish
3rd rowArabic (South Levantine Spoken)
4th rowPersian
5th rowPortuguese
ValueCountFrequency (%)
albanian 2
 
9.5%
urdu 2
 
9.5%
lao 1
 
4.8%
croatian 1
 
4.8%
southern 1
 
4.8%
pashto 1
 
4.8%
armenian 1
 
4.8%
tagalog 1
 
4.8%
uspanteko 1
 
4.8%
bulgarian 1
 
4.8%
Other values (9) 9
42.9%
2024-11-26T15:42:35.467858image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 23
14.7%
n 15
 
9.6%
o 10
 
6.4%
i 10
 
6.4%
r 10
 
6.4%
e 9
 
5.8%
t 7
 
4.5%
u 7
 
4.5%
l 7
 
4.5%
s 5
 
3.2%
Other values (23) 53
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 156
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 23
14.7%
n 15
 
9.6%
o 10
 
6.4%
i 10
 
6.4%
r 10
 
6.4%
e 9
 
5.8%
t 7
 
4.5%
u 7
 
4.5%
l 7
 
4.5%
s 5
 
3.2%
Other values (23) 53
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 156
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 23
14.7%
n 15
 
9.6%
o 10
 
6.4%
i 10
 
6.4%
r 10
 
6.4%
e 9
 
5.8%
t 7
 
4.5%
u 7
 
4.5%
l 7
 
4.5%
s 5
 
3.2%
Other values (23) 53
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 156
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 23
14.7%
n 15
 
9.6%
o 10
 
6.4%
i 10
 
6.4%
r 10
 
6.4%
e 9
 
5.8%
t 7
 
4.5%
u 7
 
4.5%
l 7
 
4.5%
s 5
 
3.2%
Other values (23) 53
34.0%

languages[6]
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing42899
Missing (%)> 99.9%
Memory size1.3 MiB
2024-11-26T15:42:36.001265image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length20
Median length14
Mean length13.75
Min length7

Characters and Unicode

Total characters55
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowArabic (Gulf Spoken)
2nd rowBraj Bhasha
3rd rowChinese
4th rowPunjabi (Eastern)
ValueCountFrequency (%)
arabic 1
12.5%
gulf 1
12.5%
spoken 1
12.5%
braj 1
12.5%
bhasha 1
12.5%
chinese 1
12.5%
punjabi 1
12.5%
eastern 1
12.5%
2024-11-26T15:42:37.257600image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 6
 
10.9%
n 4
 
7.3%
e 4
 
7.3%
4
 
7.3%
s 3
 
5.5%
i 3
 
5.5%
r 3
 
5.5%
h 3
 
5.5%
B 2
 
3.6%
j 2
 
3.6%
Other values (17) 21
38.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 55
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 6
 
10.9%
n 4
 
7.3%
e 4
 
7.3%
4
 
7.3%
s 3
 
5.5%
i 3
 
5.5%
r 3
 
5.5%
h 3
 
5.5%
B 2
 
3.6%
j 2
 
3.6%
Other values (17) 21
38.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 55
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 6
 
10.9%
n 4
 
7.3%
e 4
 
7.3%
4
 
7.3%
s 3
 
5.5%
i 3
 
5.5%
r 3
 
5.5%
h 3
 
5.5%
B 2
 
3.6%
j 2
 
3.6%
Other values (17) 21
38.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 55
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 6
 
10.9%
n 4
 
7.3%
e 4
 
7.3%
4
 
7.3%
s 3
 
5.5%
i 3
 
5.5%
r 3
 
5.5%
h 3
 
5.5%
B 2
 
3.6%
j 2
 
3.6%
Other values (17) 21
38.2%

languages[7]
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing42900
Missing (%)> 99.9%
Memory size1.3 MiB
2024-11-26T15:42:37.803290image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length22
Median length10
Mean length12.666667
Min length6

Characters and Unicode

Total characters38
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowArabic (Sa'idi Spoken)
2nd rowVietnamese
3rd rowTelugu
ValueCountFrequency (%)
arabic 1
20.0%
sa'idi 1
20.0%
spoken 1
20.0%
vietnamese 1
20.0%
telugu 1
20.0%
2024-11-26T15:42:39.088614image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5
 
13.2%
i 4
 
10.5%
a 3
 
7.9%
n 2
 
5.3%
u 2
 
5.3%
2
 
5.3%
S 2
 
5.3%
A 1
 
2.6%
l 1
 
2.6%
T 1
 
2.6%
Other values (15) 15
39.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 5
 
13.2%
i 4
 
10.5%
a 3
 
7.9%
n 2
 
5.3%
u 2
 
5.3%
2
 
5.3%
S 2
 
5.3%
A 1
 
2.6%
l 1
 
2.6%
T 1
 
2.6%
Other values (15) 15
39.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 5
 
13.2%
i 4
 
10.5%
a 3
 
7.9%
n 2
 
5.3%
u 2
 
5.3%
2
 
5.3%
S 2
 
5.3%
A 1
 
2.6%
l 1
 
2.6%
T 1
 
2.6%
Other values (15) 15
39.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 5
 
13.2%
i 4
 
10.5%
a 3
 
7.9%
n 2
 
5.3%
u 2
 
5.3%
2
 
5.3%
S 2
 
5.3%
A 1
 
2.6%
l 1
 
2.6%
T 1
 
2.6%
Other values (15) 15
39.5%

languages[8]
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing42901
Missing (%)> 99.9%
Memory size1.3 MiB
2024-11-26T15:42:39.635290image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length39
Median length21.5
Mean length21.5
Min length4

Characters and Unicode

Total characters43
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowArabic (Eastern Egyptian Bedawi Spoken)
2nd rowUrdu
ValueCountFrequency (%)
arabic 1
16.7%
eastern 1
16.7%
egyptian 1
16.7%
bedawi 1
16.7%
spoken 1
16.7%
urdu 1
16.7%
2024-11-26T15:42:40.913535image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
 
9.3%
4
 
9.3%
n 3
 
7.0%
i 3
 
7.0%
e 3
 
7.0%
r 3
 
7.0%
d 2
 
4.7%
E 2
 
4.7%
t 2
 
4.7%
p 2
 
4.7%
Other values (15) 15
34.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 43
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4
 
9.3%
4
 
9.3%
n 3
 
7.0%
i 3
 
7.0%
e 3
 
7.0%
r 3
 
7.0%
d 2
 
4.7%
E 2
 
4.7%
t 2
 
4.7%
p 2
 
4.7%
Other values (15) 15
34.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 43
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4
 
9.3%
4
 
9.3%
n 3
 
7.0%
i 3
 
7.0%
e 3
 
7.0%
r 3
 
7.0%
d 2
 
4.7%
E 2
 
4.7%
t 2
 
4.7%
p 2
 
4.7%
Other values (15) 15
34.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 43
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4
 
9.3%
4
 
9.3%
n 3
 
7.0%
i 3
 
7.0%
e 3
 
7.0%
r 3
 
7.0%
d 2
 
4.7%
E 2
 
4.7%
t 2
 
4.7%
p 2
 
4.7%
Other values (15) 15
34.9%

languages[9]
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing42902
Missing (%)> 99.9%
Memory size1.3 MiB
2024-11-26T15:42:41.447452image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters31
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowArabic (North Levantine Spoken)
ValueCountFrequency (%)
arabic 1
25.0%
north 1
25.0%
levantine 1
25.0%
spoken 1
25.0%
2024-11-26T15:42:42.643245image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3
 
9.7%
3
 
9.7%
n 3
 
9.7%
t 2
 
6.5%
a 2
 
6.5%
i 2
 
6.5%
o 2
 
6.5%
r 2
 
6.5%
k 1
 
3.2%
p 1
 
3.2%
Other values (10) 10
32.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 31
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 3
 
9.7%
3
 
9.7%
n 3
 
9.7%
t 2
 
6.5%
a 2
 
6.5%
i 2
 
6.5%
o 2
 
6.5%
r 2
 
6.5%
k 1
 
3.2%
p 1
 
3.2%
Other values (10) 10
32.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 31
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 3
 
9.7%
3
 
9.7%
n 3
 
9.7%
t 2
 
6.5%
a 2
 
6.5%
i 2
 
6.5%
o 2
 
6.5%
r 2
 
6.5%
k 1
 
3.2%
p 1
 
3.2%
Other values (10) 10
32.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 31
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 3
 
9.7%
3
 
9.7%
n 3
 
9.7%
t 2
 
6.5%
a 2
 
6.5%
i 2
 
6.5%
o 2
 
6.5%
r 2
 
6.5%
k 1
 
3.2%
p 1
 
3.2%
Other values (10) 10
32.3%

Interactions

2024-11-26T15:41:45.940061image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Correlations

2024-11-26T15:42:43.059073image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
languages[4]zipcode
languages[4]1.0000.328
zipcode0.3281.000

Missing values

2024-11-26T15:41:46.897722image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-26T15:41:48.716535image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-11-26T15:41:50.215915image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

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0674595d263f3d792c14081ceKyleNaNSeybothThe Seyboth TeamNaNNaNNaN969 Waterman AveEast ProvidenceRIUnited States2914(401) 477-0124(508) 726-3492NaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/kyle-seyboth-P80096892NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1674595d263f3d792c14081cfWilliamNaNLublinAdvantage GoldNaN1997 GPAR REALTOR of the Year Inducted to Greater Phila. Association of REALTORS Hall of Fame Certified Real Estate Instructor BILL LUBLIN operates a successful multi-office real estate firm and has been recognized as a thought leader for his insights regarding technology and its use in business. An international speaker and trainer, he makes complicated things simple in a fast paced entertaining manner. Entering the real estate business in 1971 at the age of 21, Bill rapidly gained recognition as one of the best salespeople in the marketplace. From his earliest days he began a career of service to both the community and the industry, always embracing the latest tools and technology. Bill has served as a member of the National Association of REALTORS Professional Standards Committee and Risk Management Committee. He was also appointed to serve on the Interpretations and Procedures Sub-Committee, the Article 10 Standards Revision Working Group, the Commercial Membership Recruitment Group, the BPO Workgroup, and was appointed Chair of the NAR Short Sale Workgroup. In addition Bill has was Vice-Chair of the Professional Standards Forum and the Professional Standards Committee, was Chairman of the Committee in 2008, the Association's Centennial Year, and chairing the Interpretations and Procedures Sub-Committee of Professional Standards in 2009 . In 2014 Bill will serve as the Chair for the MLS Issues & Policies Committee for NAR.https://www.century21.com/c21/remote-media/affiliate-4x5-316w/aa0/aed/c6/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvdmc0ZjF5NG4xemJzbTJ5aDlqZGR4N3FuZjdp.jpg494 Second Street PikeSouthamptonPAUnited States18966(215) 671-4701(215) 280-4114NaNNaNhttps://search.c21ag.com/idx/agent/159361/bill-lublinhttps://www.century21.com/real-estate-agent/profile/william-lublin-P10058887NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2674595d263f3d792c14081d0FerminNaNGroupNorth EastNaNNaNNaN130 Parker StLawrenceMAUnited States1843(800) 844-7653(978) 423-6545NaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/michelle-fermin-of-fermin-group-of-fermin-group-P25361165NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3674595d263f3d792c14081d121MikeTeamHomeStarNaNNaNhttps://www.century21.com/c21/remote-media/affiliate-4x5-316w/55e/8aa/2d/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvN2MwYThnOTlxemoxbXhhdDJ4MGdqYzBiMjBp.jpg31320 Solon RoadSolonOHUnited States44139(440) 449-9100(216) 373-7727NaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/mike-ferrante-of-21-mike-team-of-21-mike-team-P25301173SpanishEnglishNaNNaNNaNNaNNaNNaNNaNNaN
4674595d263f3d792c14081d2TheMillsGroupBarefoot RealtyNaNNaNNaN4720 Barefoot Resort Bridge RoadNorth Myrtle BeachSCUnited States29582(843) 390-1999(843) 213-8754NaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/kevin-mills-of-the-mills-group-of-the-mills-group-P25382693NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
5674595d263f3d792c14081d3TimNaNWilliams803 RealtyNaNLexington is where Tim Williams, owner and broker-in-charge at 803 Realty , grew up. 803 Realty offers a stress-free approach to buying and selling real estate through partnerships with industry leaders throughout the purchasing or selling process. These partnerships and connections allow clients to feel at ease and know that every step of the process is being held with the utmost care and urgency. The agency has also partnered with a property management company that allows for their clients to have a one stop approach to real estate. 803 Realty rebranded in June of 2020, after first opening its doors as Williams Real Estate Group in January 2016 as a full service residential real estate company. Tim and the other 42 agents pride themselves on their VIP client level customer service. They are selling homes 25 days faster than the Midlands average and operate as a one stop shop for both real estate sales and rentals. Tim is continually expanding to service communities throughout the 803 area code. He recently announced the expansion of their sales force to the Aiken/North Augusta market. The agency continues to focus on finding new ways to serve the community by joining multiple charitable foundations and business leaders that work to beautify the town and encourage growth and diversity. Everyday, Tim gets to help individuals and families with one of the largest purchases of their life, real estate. Not only that, but he also gets to mentor agents who work with 803 Realty and learn new ways to serve the community and build the business. Tim is grateful how his work in this service industry has touched his life. He shared that life is a beautiful thing that we must all be grateful for and that success should be defined by the individual, not a company or corporation. I feel as though in this industry and in any 'luxury industry' there is too much pressure on agents to work towards driving a certain car or making a certain amount of money, he said. We all have different levels of comfort when it comes to living and different things we are working toward. I feel as though it's important as a company that we promote that individuality because that's what makes this community thrive and great. 803 Realty will always remain locally owned and operated, putting their clients and community first. Visit 803 Realty at 5599 Sunset Boulevard or at www.803realtylexington.com . Tim and his wife Cidney, are quite involved in Lexington, from helping out at the schools their four children attend to taking part in city beautification projects. They also love Lake Murray - the jewel of South Carolina. I love time with my family and vacationing, Tim adds. They are the center of my world.https://www.century21.com/c21/remote-media/affiliate-4x5-316w/052/e33/91/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMjI4aTAvMXF6dGhnbTR4eGR0NGQya2hha3ExYzY1Zzdp.jpg5599 Sunset BlvdLexingtonSCUnited States29072(803) 490-1877(803) 528-9219NaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/tim-williams-P80133938NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
6674595d263f3d792c14081d4ShellyNaNGarner803 RealtyNaNShelly Garner is a local Realtor with 24 years experience in the Lexington and Columbia Area. Shelly has ranked in the Real Trends Top 1,000 agents nationally for the past 4 years. Shelly has a real passion for new homes sales and over the past 8 years has been honored to have achieved being the top sales agent for a local builder. Shelly is committed to helping you buy or sell your home with the highest level of expertise in your local market. Shelly creates a positive experience for both sides in any real estate transaction. Known by clients and colleagues alike for her honesty, perseverance and professionalism, she has a reputation for a quick, timely response to each client's needs and concerns. Shelly has the market knowledge as well as negotiation and communication skills to provide exceptional customer satisfaction, which is her personal commitment to each and every client. Give Shelly a Call or Email she would love to assist you with your real estate needs.https://www.century21.com/c21/remote-media/affiliate-4x5-316w/1c9/668/16/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMjI4aTAvZzRzZ2R6cGpzOWR0bW10MWcycGR4NzVndjRp.jpg5599 Sunset BlvdLexingtonSCUnited States29072(803) 490-1877(803) 309-9527NaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/shelly-garner-P80134444NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
7674595d263f3d792c14081d5EdnaNaNKimbleWright Real EstateNaN#1 Century 21 Realtor in The United States #1 Century 21 realtor in Oklahoma for the past 5 years #1 Realtor in Tahlequah Best of the Best for the past several years #1 in Customer Service for the past 5 years ABR, SRS, CRS, GRI, CHMS A Home SOLD Every 2.1 dayshttps://www.century21.com/c21/remote-media/affiliate-4x5-316w/18b/030/4f/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvbjhocndlZzh4NzUybTN0eHZlMW05anhtODJp.jpg103 Mimosa LnTahlequahOKUnited States74464(918) 456-5288(918) 931-8413NaNNaNhttp://www.ednakimble.com/https://www.century21.com/real-estate-agent/profile/edna-kimble-P25273278NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
8674595d263f3d792c14081d6ScheetzNaNTeamScheetzNaNMike and Melanie Scheetz began serving the greater Indianapolis area residential real estate community over two decades ago in 1995. With over 20 years of experience and the beneficial insight of a male and female team, Mike and Melanie offer service that is set apart from the rest with their unparalleled knowledge, experience, and insightful expertise. Choosing Mike and Melanie Scheetz will not only provide a stress-free buying and selling experience, but a lasting relationship with people who care more about the relationships they'll build than the commission they'll earn.https://www.century21.com/c21/remote-media/affiliate-4x5-316w/6b1/69d/4f/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvdnZ4MzJwcDhnNGhoNHlqcGphZ3Q2NXczNDRp.jpg270 East Carmel DriveCarmelINUnited States46032(317) 844-5111(317) 587-8600(317) 814-2100NaNhttp://scheetzteam.com/https://www.century21.com/real-estate-agent/profile/mike-scheetz-of-scheetz-team-of-scheetz-team-P10143053NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
9674595d263f3d792c14081d7TheEliteTeamEverestNaNNaNhttps://www.century21.com/c21/remote-media/affiliate-4x5-316w/d1f/a93/eb/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvMWZ5Z2NyNjF6aGh0bTl0ZHI3MzM0czc3ZDdp.jpg6925 S. Union Park Center, Suite 600Cottonwood HeightsUTUnited States84047(801) 449-3000(801) 910-5087NaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/david-parker-of-the-elite-team-of-the-elite-team-P25361741NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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42893674595e363f3d792c141295cJulioNaNPachecoRealty MastersNaNNaNNaN11716 Rosecrans AvenueNorwalkCAUnited States90650(562) 677-1800NaNNaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/julio-pacheco-P25396833SpanishEnglishNaNNaNNaNNaNNaNNaNNaNNaN
42894674595e363f3d792c141295dEddieNaNPachecoAllPoints RealtyNaNNaNhttps://www.century21.com/c21/remote-media/affiliate-4x5-316w/a99/b51/61/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAveGpiZjhwOTZ3dmh6NGNld25rNXoxZHR6ZTVp.jpg476 Naubuc Ave.GlastonburyCTUnited States6033(860) 646-4525(860) 490-5405NaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/eddie-pacheco-P80180200NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42895674595e363f3d792c141295eRobertNaNPachenceSelect GroupNaNNaNNaN702 North Church StreetHazletonPAUnited States18201(570) 455-8521(570) 401-3773(570) 455-8521NaNNaNhttps://www.century21.com/real-estate-agent/profile/robert-pachence-P25285130NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42896674595e363f3d792c141295fJosephNaNPacilioVillage RealtyNaNAbout Joe Pacilio Passion, knowledge, experience and commitment. Meet Joe Pacilio, a Real Estate Agent and Runner who is an active Member of the Community and a Top Producer at Century 21. What separates Joe Pacilio from the pack? His passion for success, knowledge in the industry, experience in the community, and his commitment to you. As a trusted member of the real estate community, Joe served as the 2015 President of the Arcadia Association of Realtors, A Board of Director for California Association of Realtors from 2014 through 2018 2016 REALTOR of The Year by The Arcadia Association of REALTORS Working with Joe means working with Century 21 Village Realty. Century 21 Village Realty is a force to be reckoned with in the Southern California Real Estate Industry. With any passion comes the desire to not only participate, but to actively contribute. As a Runner and a leader, Joe spends his free time doing what he loves most, giving back, and running of course. He is the Team Captain for the American Cancer Society Relay for Life since 2008, active member of the Mt. Wilson Trail Race Committee since 2010, a Rose Parade Float Operator since 2004, and a participant in many local races including Mt. Wilson Trail Race, LA Marathon, Santa Anita Derby Day, to name a few. As a Real Estate Agent / Runner AND active Member of the community, this triple threat is a master at his craft and is sure to be by your side from the Start to the Finish Line Joe is with you every step of the way.https://www.century21.com/c21/remote-media/affiliate-4x5-316w/b43/e7c/f0/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvODJoZzB3NXc1Z25xNDBlcjg3bTl3Y2phZTNp.jpg38 West Sierra Madre Blvd.Sierra MadreCAUnited States91024(626) 355-1451(626) 589-8945NaNNaNhttps://www.joepacilio.com/https://www.century21.com/real-estate-agent/profile/joseph-pacilio-P80133843NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42897674595e363f3d792c1412960SergioNaNPachecoRealty MastersNaNNaNhttps://www.century21.com/c21/remote-media/affiliate-4x5-316w/a53/4cd/ce/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvajZuajFzNTBybTdkNG5qMTN2enQxMnB2cjNp.jpg830 N Wilcox AveMontebelloCAUnited States90640(323) 722-7300(323) 722-7300(213) 760-1904NaNhttps://www.sergiopacheco.comhttps://www.century21.com/real-estate-agent/profile/sergio-pacheco-P99428577NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42898674595e363f3d792c1412961AraceliNaNRiveraKingNaNNaNNaN8338 Day Creek Blvd.Rancho CucamongaCAUnited States91739(909) 980-8000(626) 384-1208NaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/araceli-rivera-P80167551EnglishSpanishNaNNaNNaNNaNNaNNaNNaNNaN
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42900674595e363f3d792c1412963AshleyNaNTrowbridgeJudge Fite CompanyNaNNaNhttps://www.century21.com/c21/remote-media/affiliate-4x5-316w/6d2/7d4/50/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMjI4aTAvNTExcGVlMjNwYWRlbTRhNXNlZjBicGp6djJp.jpg117 N. Dallas StEnnisTXUnited States75119(972) 875-5867(903) 654-9971NaNNaNhttp://www.ashleytrowbridge.sites.c21.homes/https://www.century21.com/real-estate-agent/profile/ashley-trowbridge-P80180301NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42901674595e363f3d792c1412964JoannaNaNValenzuelaA Better Service RealtyNaNNaNhttps://www.century21.com/c21/remote-media/affiliate-4x5-316w/659/6bb/43/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xMTAzaTAvY2czNWZzbWJ3am1tbTR5OXB0c2Z0NmhzaDNp.jpg8077 Florence AvenueDowneyCAUnited States90240(562) 806-1000(562) 964-0778NaNNaNNaNhttps://www.century21.com/real-estate-agent/profile/joanna-valenzuela-P80136879EnglishSpanishNaNNaNNaNNaNNaNNaNNaNNaN
42902674595e363f3d792c1412965ScottNaNWillisAmerican PropertiesNaNNaNhttps://www.century21.com/c21/remote-media/affiliate-4x5-316w/3f6/93f/e5/aHR0cHM6Ly9jMjEuYXp1cmVlZGdlLm5ldC8xN2kwLzRhY250eXR4NnN3bm0zNnFwcXFtMWhxbngyaQ.jpg1935 Lejeune BoulevardJacksonvilleNCUnited States28546(910) 577-5400(910) 577-5400NaNNaNhttp://www.jacksonvillerealestatenc.com/https://www.century21.com/real-estate-agent/profile/scott-willis-P10177777NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN